GitHub
mithril-checkpoint-agent
Build mithril-checkpoint compression for PyTorch models. Use when implementing byte grouping, compression pipeline, or checkpoint I/O.
Skills IA Bases de données
Découvrez les skills Bases de données, comparez leurs dépôts et consultez leurs instructions.
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GitHub
security-scan-local
Run security scans locally (Semgrep, Trivy, Gitleaks) to detect vulnerabilities, secrets, and code issues before pushing. Use when the user wants to check for security issues, scan dependencies, or validate cod...
GitHub
rust-project-setup
Initialize Rust projects with proper structure, essential crates, and Cargo.toml configuration. Use when starting new Rust binaries or libraries.
GitHub
git-worktree-manager
Manage Git worktrees for parallel feature development. Use when the user wants to work on multiple branches simultaneously, create worktrees, switch between features, open terminals/editors for worktrees, or ma...
GitHub
rust-async-testing
Write async tests with tokio::test and configure multi-threaded test runtimes. Use when testing async code.
GitHub
rust-async-concurrency
Manage concurrent operations with channels, semaphores, locks, and streams. Use when coordinating parallel work or limiting resource usage.
GitHub
rust-candle-core
Build native Rust ML models with Candle framework. Use when implementing vision transformers, LLMs, or audio models with GPU acceleration.
GitHub
mithril-dedup-agent
Build mithril-dedup for ML dataset deduplication. Use when implementing MinHash, LSH, clustering, or document I/O.
GitHub
rust-candle-whisper
Implement native Rust ML inference with Candle framework. Use when building GPU-accelerated ML pipelines without Python dependencies.
GitHub
rust-code-organization
Structure Rust code using modules, traits, builders, and newtypes. Use when designing APIs, abstracting behavior, or preventing type confusion.
GitHub
mithril-cache-agent
Build mithril-cache for torch.compile caching. Use when implementing content-addressable storage, cache keys, eviction, or framework hooks.
GitHub
rust-mocking
Create mocks using mockall and trait-based abstractions. Use when unit testing code with external dependencies.
GitHub
rust-ml-huggingface-porting
Port HuggingFace models to Candle with correct tensor naming. Use when debugging weight loading errors or matmul issues.
GitHub
skill-creator
Create new Claude Code skills with proper structure and conventions. Use when the user wants to create a new skill, scaffold skill templates, or understand skill anatomy.
GitHub
rust-code-quality
Apply rustfmt and clippy linting standards for consistent, safe Rust code. Use before commits and in CI pipelines.
GitHub
rust-metrics
Expose Prometheus metrics with counters, gauges, and histograms. Use for production monitoring and alerting.
GitHub
rust-repository
Implement the repository pattern for database abstraction with sqlx, transactions, and retry logic. Use when building data access layers.
GitHub
rust-tokio-essentials
Core Tokio patterns including runtime setup, spawn_blocking for CPU work, and avoiding blocking operations. Use for any async Rust development.
GitHub
rust-error-handling
Design error types using thiserror for libraries and anyhow for applications. Use when defining error hierarchies or handling fallible operations.
GitHub
lint-service
Unified linting scripts for all services in the monorepo. Use when the user wants to lint code, check formatting, or run type checks.
GitHub
rust-graceful-shutdown
Implement graceful shutdown with signal handling and broadcast channels. Use when building long-running services or daemons.
GitHub
rust-release-profile
Configure release builds for maximum performance with LTO, optimizations, and binary stripping. Use for production deployments.
GitHub
rust-pyo3-bridge
Bridge Rust and Python using PyO3 with proper GIL handling and async compatibility. Use when integrating Python ML models or libraries.
GitHub
rust-s3-patterns
Implement S3 operations with rust-s3 including streaming downloads, multipart uploads, and batch operations. Use for cloud storage integration.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.